# Manus vs OpenCrab

Manus records 19,195,779 monthly visits with -1.7% month-over-month growth and Free Trial pricing. OpenCrab records 0 monthly visits with -100% growth and Freemium pricing.

| Metric | [Manus](https://openaitools.app/tool/manus) | [OpenCrab](https://openaitools.app/tool/opencrab) |
| :--- | :--- | :--- |
| Website URL | https://manus.im | https://opencrab.sh |
| Categories | AI Assistant, AI Agent, AI Copilot | AI Knowledge Graph, AI Agent, AI Research Tool |
| Pricing Model | Free Trial | Freemium |
| Monthly Visits | 19,195,779 | 0 |
| MoM Growth Rate | -1.7% | -100% |
| Primary Market | Brazil | Global |
| Direct Visits | 10,563,180 | 0 |
| Review Score | 4.6 | 4.1 |
| Saved Count | 10 | 0 |
| Supported Platforms | Website | Website |

## Manus

Manus positions itself as an "action engine" rather than a chatbot. You describe an outcome, and the agent breaks it into steps, decides which tools to use, browses the web when it needs current information, and assembles the final deliverable in a cloud sandbox. Typical outputs include presentation decks, working websites and small games, generated images and video, and long-form research reports assembled through its Wide Research workflow.

The product ships as a mobile app (iOS and Android), a desktop app, and a browser extension, plus a web console with an API for programmatic use. A Slack integration lets teams dispatch tasks from chat, and workspace features such as team plans and SSO make it viable inside organizations rather than only for individuals. Because the agent runs asynchronously, a common pattern is to queue a task, walk away, and review the result later.

Pricing combines a free trial-style entry point with paid subscription tiers and a business plan; exact credit allowances and seats change over time, so confirm current terms on the official pricing page. The obvious trade-off is control: autonomous agents can misread intent or burn credits on the wrong approach, so clear briefs and intermediate review matter.

**Pricing & Plans:** Free trial available, with paid subscription tiers and a business plan for teams and higher usage. Credit allowances and seat details change, so check the official pricing page.

- **Autonomous task execution:** Give the agent a goal and it plans the steps, chooses tools, and works through the task in a cloud environment without constant supervision.
- **Deliverable generation:** Produces finished artifacts such as slide decks, functional websites, small games, and formatted documents rather than raw text.
- **Wide Research:** Runs broad, multi-source investigations and compiles the findings into a structured report.
- **Media creation:** Generates images, video, and music as part of a larger task or as standalone outputs.
- **Integrations and API:** Connects to Slack for task dispatch, offers mobile and desktop apps, and exposes an API for embedding agent work in your own stack.

**Strengths:** Delivers finished artifacts instead of only conversational answers; Works across web, mobile, desktop, Slack, and API surfaces; Wide Research handles broad multi-source investigations well; Team plans and SSO make it usable in organizational settings

**Limitations:** Autonomous runs consume credits and can pursue the wrong approach if the brief is vague; Complex tasks benefit from human review at checkpoints; Output quality varies by task type, especially outside common formats

[Profile (Markdown)](https://openaitools.app/tool/manus.md)

## OpenCrab

OpenCrab is built around a simple idea: knowledge should be structured as a graph before agents reason over it. You feed the platform documents, URLs, notes or code, and it handles the unglamorous work of parsing, OCR and chunking. From there it extracts entities, concepts, evidence, relationships and claims, weaving them into a source-attributed ontology graph.

The second half of the product is reuse. Graphs can be saved as versioned ontology packs, shared with teammates, or published and sold through the marketplace. A researcher can turn a stack of papers into a queryable, citation-backed graph; a domain expert can package their know-how as a sellable pack; an AI builder can wire the graph into an agent as long-term memory.

The connector layer is what ties it together. A single MCP server means Claude, ChatGPT, Cursor, Codex and other clients all see the same graph, so grounded retrieval travels with you across tools rather than being locked in one workspace. Pricing starts free, with paid tiers for private ingestion and pack publishing.

**Pricing & Plans:** Free tier at $0/month for exploring and sharing public ontology packs and basic graph queries. Pro is $10/month for private document ingestion and a personal graph RAG workspace. Expert is $30/month for pack publishing workflows and MCP reverse ingest. Billing is handled securely via Paddle and can be changed at any time.

- **Document ingestion and parsing:** Upload documents, URLs, notes or code and let the platform handle parsing, OCR and chunking automatically.
- **Ontology graph construction:** Extract entities, concepts, evidence, relationships and claims into a graph where every node traces back to a source.
- **Reusable ontology packs:** Bundle a graph into a versioned, reusable pack you can share with your team or sell in the marketplace.
- **MCP server integration:** One MCP server lets Claude, ChatGPT, Cursor, Codex and other clients query the same graph.
- **Graph RAG querying:** Retrieve grounded, cited answers from your graph instead of relying on a model's memory alone.

**Strengths:** Turns unstructured documents into a source-attributed graph rather than a flat vector index; MCP server means the same grounded knowledge works across Claude, ChatGPT, Cursor and Codex; Ontology packs are reusable, shareable and sellable, creating value beyond a single project; CRUD-style tiers are affordable, with a genuinely usable free level

**Limitations:** Some features (pack publishing, MCP reverse ingest) are gated behind the Expert tier; Best value requires feeding it well-structured documents; messy inputs limit graph quality; The public library and marketplace are still relatively young, so niche ontologies may be sparse

[Profile (Markdown)](https://openaitools.app/tool/opencrab.md)

## Frequently Asked Questions

### How do Manus and OpenCrab compare in monthly traffic?

Manus has 19,195,779 monthly visits, while OpenCrab has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Manus has a month-over-month growth rate of -1.7%; OpenCrab has -100%.

### How does pricing compare?

Manus: Free Trial. Free trial available, with paid subscription tiers and a business plan for teams and higher usage. Credit allowances and seat details change, so check the official pricing page. OpenCrab: Freemium. Free tier at $0/month for exploring and sharing public ontology packs and basic graph queries. Pro is $10/month for private document ingestion and a personal graph RAG workspace. Expert is $30/month for pack publishing workflows and MCP reverse ingest. Billing is handled securely via Paddle and can be changed at any time.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [ChatGPT](https://openaitools.app/tool/chatgpt-4) | 6,048,022,723 | +2.2% | Freemium | Provides powerful reasoning agents and deep research, but lacks Manus's specialized continuous cloud workspace execution. | [.md](https://openaitools.app/tool/chatgpt-4.md) |
| 2 | [Claude](https://openaitools.app/tool/claude-2) | 1,253,439,413 | +23.8% | Freemium | Features advanced computer use and interactive artifacts, but operates primarily as a chat assistant rather than a dedicated autonomous agent platform. | [.md](https://openaitools.app/tool/claude-2.md) |
| 3 | [Notion](https://openaitools.app/tool/t) | 173,441,670 | +0.1% | Freemium | The AI workspace where teams and agents get work done together | [.md](https://openaitools.app/tool/t.md) |
| 4 | [Muse](https://openaitools.app/tool/muse-ai-1) | 45,751,822 | +228.3% | Contact for Pricing | Executes tasks using cloud virtual Linux machines, but focuses more on personal desktop automation than complex multi-app research. | [.md](https://openaitools.app/tool/muse-ai-1.md) |
| 5 | [Hermes-Agent](https://openaitools.app/tool/hermes-agent-1) | 3,638,741 | -5.4% | Freemium | Provides open-source personal task automation, but lacks the polished cloud sandbox environment of Manus. | [.md](https://openaitools.app/tool/hermes-agent-1.md) |
| 6 | [Runable](https://openaitools.app/tool/runable) | 1,048,370 | -1.9% | Freemium | Automates multi-step workflows and asset creation, but with fewer built-in general browser navigation tools. | [.md](https://openaitools.app/tool/runable.md) |
| 7 | [Skywork.ai](https://openaitools.app/tool/skywork-ai) | 1,021,069 | -11.8% | Freemium | Converts prompts into structured office deliverables, but acts primarily as a document generation workspace. | [.md](https://openaitools.app/tool/skywork-ai.md) |
| 8 | [Connected Papers](https://openaitools.app/tool/connected-papers) | 750,576 | +3.1% | Freemium | Explore the academic literature as a visual graph of related papers | [.md](https://openaitools.app/tool/connected-papers.md) |
| 9 | [LlamaIndex](https://openaitools.app/tool/llamaindex) | 387,910 | +19.9% | Freemium, Contact for Pricing | Turn any document into AI-ready context with agentic parsing and extraction | [.md](https://openaitools.app/tool/llamaindex.md) |
| 10 | [LibreChat](https://openaitools.app/tool/librechat) | 346,879 | -3.5% | Free | Unites multiple models and custom agents in a self-hosted workspace, but lacks pre-built autonomous execution sandboxes. | [.md](https://openaitools.app/tool/librechat.md) |

---
Source: https://openaitools.app/compare/manus-vs-opencrab

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)